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Section 1: Overview
Name of Research Project
Related Project
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Part
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GWF-NGS: Next Generation Solutions for Healthy Water Resources
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Program Affiliations
Related Research Project(s)
GWF-NGS: Next Generation Solutions for Healthy Water Resources | |
Dataset Title
Measuring Virus Indicators in Wastewater as an Early Warning of COVID-19 Outbreaks
Additional Information
Creators and Contributors
Patrick D’Aoust | | | University of Ottawa |
Jean-Baptiste Burnet | | | Polytechnique Montréal |
Robert Delatolla | | | University of Ottawa |
Sarah Dorner | | | Polytechnique Montréal |
Qiudi Geng | | | Great Lakes Institute for Environmental Research, University of Windsor |
John P. Giesy Jr. | | | Veterinary Biomedical Sciences & Toxicology Centre, University of Saskatchewan |
Melissa Glier, | | | BC Centre for Disease Control |
Eyerusalem Goitom | | | Polytechnique Montréa |
Chand Mangat | | | National Microbiology Laboratory, Public Health Agency of Canada |
Robert (Mike) McKay | | | Great Lakes Institute for Environmental Research, University of Windsor |
Xiaoli (Lilly) Pang | | | Public Health Laboratory - Alberta Precision Laboratory, University of Alberta |
Natalie Prystajecky | | | C Centre for Disease Control,University of British Columbia |
Judy Yuanyuan Qiu | | | University of Alberta |
Mark Servos | | | University of Waterloo |
Nivetha Srikanthan | | | University of Waterloo |
Yuanmin Wu | | | Great Lakes Institute for Environmental Research/S.M. Research Inc. |
Yuwei Xie | | | Toxicology Centre, University of Saskatchewan |
Abstract
Purpose
To characterize the inter- and intra- laboratory variability associated with results emanating from quantifying RNA of SARS-CoV-2 using RT-qPCR after extraction from a common wastewater matrix. This study was conducted in collaboration with the National Microbiology Laboratory (NML) in Winnipeg, Manitoba. Seven Canadian laboratories (located in in Vancouver, Edmonton, Saskatoon, Windsor, Waterloo, Ottawa and Montreal) that had already demonstrated experience and capacity to analyze SARS-CoV-2 RNA in wastewater by RT-qPCR were selected to participate.
To inform the user sector about the potential of local/provincial/national SARS-CoV-2 wastewater surveillance programs to support public health decision-making, which not only relies on sufficient laboratory capacity, but also a coordinated effort to elucidate method-specific biases and limitations associated with the data acquired. Although various protocols have been established for concentration, extraction and analysis of SARS-CoV-2 RNA from wastewater, how these differing protocols perform for a common wastewater matrix has not been investigated.
This study involves characterizing the apparent recovery (including its variability) of spiked SARS-CoV-2 surrogates in a single, common wastewater matrix, which were provided blind by NML to a cross-section of seven Canadian laboratories with demonstrated capacity to analyze SARS-CoV-2 by RT-qPCR. The goal was to infer at a high level some of the key biases and considerations associated with estimation of SARS-CoV-2 RNA concentrations in wastewater and to recommend coordinated approaches for analysis and reporting.
Plain Language Summary
Most people with COVID-19 start shedding SARS-CoV-2 through their stool within 24 hours of being infected. This “viral signal” detected in wastewater helps provide population-level estimates of the rate of infection in a municipality, indicating whether the number of infected people in Saskatoon is increasing, decreasing or staying the same. Even a few days of early warning in communities can be critical to the success of pandemic preparedness measures, especially for rapidly evolving variants.
The viral wastewater signal is a leading indicator of impending surges in numbers of active cases that precede increases in new positive cases by seven to 10 days. By gathering this information which in effect surveys all of the individuals connected to the wastewater collection system, the team and its partners are able to warn of upcoming increases in positive cases.
This information on the level of the coronavirus genetic material (known as RNA) complements testing performed on individuals (swab testing) that is the centerpiece of COVID-19 surveillance strategies globally.
Swab tests are limited by the fact that COVID-19 symptoms might not appear for as many as five days after infection. These tests do not capture cases of people who are already infected but do not yet show symptoms (pre-symptomatic), or those who show no symptoms at all (asymptomatic), or only very mild ones (oligosymptomatic). As well, not everyone with COVID-19 is tested, and obtaining results can take time.
The research team has also begun to screen Saskatoon’s wastewater for the B.1.1.7 variant of concern (VOC) first detected in the U.K. in September of 2020. Additional variants will be added to the panel as the situation evolves.
This variant tracking data should be seen merely as an indicator of trends which need to be verified using sequencing technology through the Public Health Agency of Canada. Because individuals are at varying stages of infection when shedding the virus, the variant levels detected in sewage are not necessarily directly comparable to the proportion of variant cases found in individual swab samples confirmed through provincial genetic sequencing efforts.
USask is now designated as the Prairie Node of PHACs Canada-wide WBE efforts and has expanded to testing wastewater from other communities in Saskatchewan, including five First Nations in collaboration with the Indigenous Technical Services Cooperative. The team has also successfully participated in an interlab comparison study coordinated by the Canadian Water Network.
Keywords
COVID-19 |
SARS-CoV-2 |
HCoV-229E |
Wastewater |
Canadian Water Network |
eDNA |
Citations
Section 3: Status and Provenance
Dataset Version
Dataset Creation Date
Status of data collection/production
Dataset Completion or Abandonment Date
Data Update Frequency
Creation Software
Primary Source of Data
Other Source of Data (if applicable)
Data Lineage (if applicable). Please include versions (e.g., input and forcing data, models, and coupling modules; instrument measurements; surveys; sample collections; etc.)
Section 4: Access and Downloads
Access to the Dataset
Terms of Use
Does the data have access restrictions?
Downloading and Characteristics of the Dataset
Download Links and Instructions
Total Size of all Dataset Files (GB)
File formats and online databases
Other Data Formats (if applicable)
List of Parameters and Variables